Proceedings

EPJ Data Science Highlight - Driven by friendship

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© Emilio Ferrara

Dynamics of Facebook: the structure of the network drives friends to congregate into many small, highly interconnected communities

For the first time, the dynamics of how Facebook user communities are formed have been identified, revealing surprisingly few large communities and innumerable highly connected small-size communities. These findings are about to be published in EPJ Data Science by Italian scientist Emilio Ferrara, affiliated with both Indiana University in Bloomington, Indiana, USA and his home University of Messina. This work could ultimately help identify the most efficient way to spread information, such as advertising, or ideas over large networks.

No previous work has attempted to analyse the community structure of Facebook as a proxy to understanding real world communities at the same scale.

The author elected to analyse Facebook with the mathematical tools typically used to study complex systems in order to uncover its dynamics. First, Ferrara acquired a snapshot of the structure of the users’ friendship network using several techniques of statistical sampling applied to the anonymised public profiles of Facebook users. He then validated his approach to detect communities by comparing the outcome of several statistical methods and by using various algorithms.

He found that Facebook communities emerge as a result of the network’s structure, which is based on creating networks of friends. It therefore has little to do with how individual users behave. Ferrara also realised that only few large communities emerge. Instead, users tend to aggregate in small-sized communities that are extremely interconnected. This type of structure is known to optimise the efficiency of communications among users. Indeed, short paths of communication can connect any pair of users, even if they belong to completely disparate communities.

Ultimately, this approach could be applied to verify a social theory known as Granovetter’s "strength of weak ties", whereby loose interconnections among users yield better opportunities and more efficient communication channels.

A large-scale community structure analysis in Facebook. E. Ferrara (2012), EPJ Data Science 1:9, DOI 10.1140/epjds9

This was our first experience of publishing with EPJ Web of Conferences. We contacted the publisher in the middle of September, just one month prior to the Conference, but everything went through smoothly. We have had published MNPS Proceedings with different publishers in the past, and would like to tell that the EPJ Web of Conferences team was probably the best, very quick, helpful and interactive. Typically, we were getting responses from EPJ Web of Conferences team within less than an hour and have had help at every production stage.
We are very thankful to Solange Guenot, Web of Conferences Publishing Editor, and Isabelle Houlbert, Web of Conferences Production Editor, for their support. These ladies are top-level professionals, who made a great contribution to the success of this issue. We are fully satisfied with the publication of the Conference Proceedings and are looking forward to further cooperation. The publication was very fast, easy and of high quality. My colleagues and I strongly recommend EPJ Web of Conferences to anyone, who is interested in quick high-quality publication of conference proceedings.

On behalf of the Organizing and Program Committees and Editorial Team of MNPS-2019, Dr. Alexey B. Nadykto, Moscow State Technological University “STANKIN”, Moscow, Russia. EPJ Web of Conferences vol. 224 (2019)

ISSN: 2100-014X (Electronic Edition)

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